Data Scientist

1 week ago

Riyadh, Ar Riyāḑ, Saudi Arabia TestCrew | Quality Engineering & Software Testing Full time

Key Accountabilities


• Successful delivery of production-ready ML models with measurable business impact.


• Achievement high & reliable prediction targets.


• Reduction in losses through advanced data-driven detection models.


• Improved customer retention through churn prediction and intervention strategies.


• Delivery AI/ML proof-of-concepts for emerging business opportunities.


• Clear documentation and model governance artifacts delivered for all deployed models.

Responsibilities


• Identify and prioritize AI/ML use cases that deliver measurable business value and ROI.


• Develop, validate, and deploy machine learning models for fraud detection, claim risk prediction, customer segmentation, and pricing optimization.


• Build and maintain end-to-end data pipelines, from feature engineering to model deployment.


• Implement advanced analytics techniques including deep learning, NLP, and computer vision where applicable.


• Work with ML Engineers to productionize models using MLOps best practices and CI/CD pipelines.


• Ensure compliance with PDPL and NDMO standards in data usage, model development, and AI governance.


• Implement model monitoring, drift detection, and automated retraining pipelines.


• Collaborate with stakeholders to translate complex business problems into analytical solutions.


• Conduct A/B testing and experimentation to validate model effectiveness and business impact.


• Develop explainable AI solutions to ensure model transparency and regulatory compliance.


• Prepare clear documentation, technical reports, and executive dashboards for model outcomes.


• Lead knowledge transfer sessions and mentor junior data scientists and analysts.


• Stay current with latest ML/AI research and evaluate new techniques for business applications.


• Collaborate with Data Engineering team to ensure data quality and availability for ML pipelines.


• Support the development of the enterprise ML platform and reusable components.

Knowledge and Experience


• More than 5+ years of proven experience in machine learning, data science, and applied statistics.


• Strong expertise in Python and ML frameworks (scikitlearn, TensorFlow, PyTorch, XGBoost).


• Proficiency in SQL and experience with big data platforms (BigQuery, Spark, Databricks).


• Experience with MLOps practices and tools (Kubeflow, MLflow, Vertex AI, SageMaker).


• Demonstrated ability to work with structured and unstructured data (JSON, text, images).


• Strong understanding of statistical methods, experimental design, and hypothesis testing.


• Experience in model deployment, monitoring, and lifecycle management.


• Excellent communication skills to present complex findings to technical and non-technical audiences.


• Track record of delivering end-to-end ML solutions from ideation to production.


• Insurance or financial services domain experience (fraud detection, pricing models, claims prediction).


• Knowledge of generative AI, LLMs, and their business applications.


• Experience with deep learning for computer vision and NLP applications.


• Familiarity with real-time ML serving and edge deployment.


• Experience in explainable AI (XAI) and model governance frameworks.


• Knowledge of Saudi data regulations (PDPL, NDMO, SAMA).


• Experience with cloud-native ML platforms (Vertex AI, Azure ML, SageMaker).


• Understanding of reinforcement learning and optimization algorithms.


• Contribution to open-source ML projects or research publications.


• Strong mentoring capabilities and experience leading data science teams.


• Ability to build and maintain relationships with business stakeholders.

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